Cassandra权威指南（第2版 影印版） [Cassandra the Definitive Guide] 下载 mobi epub pdf 电子书 2024

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内容简介

　　如果不用考虑可伸缩性，想象一下你能做些什么？在这本实践指南中，你将会了解到Cassandra数据库管理系统是如何在为多个数据中心提供高可用服务的同时处理上百TB的数据。扩充后的第二版已经更新到了Cassandra 3.0，书中给出了各种技术细节以及实例，当你将Cassandra投入实际生产环境时，这些内容都是必不可少的。
　　作者Jeff Carpenter和Eben Hewitt阐述了Cassandra非关系型设计的优势，着重介绍了其数据模型。
　　《Cassandra**指南（第2版 影印版）》向开发者、DBA、正在寻找数据库的可扩展性解决方案的应用架构师展示了Cassandra的速度和灵活性。

作者简介

　　Jeff Carpenter，精品国际酒店集团（Choice Hotels International）的一名系统架构师，在服务业和国防工业有着20年的从业经验。他的兴趣包括SOA/微服务、大规模系统架构设计以及数据架构。
　　EbenHewitt是精品国际酒店集团（世界大酒店之一）的首席技术官。
　　他还是好几本书籍的作者，题材涉及系统架构、分布式系统以及编程。

内页插图

目录

Foreword
Foreword
Preface

1．Beyond Relational Databases
What's Wrong with Relational Databases?
A Quick Review of Relational Databases
RDBMSs： The Awesome and the Not-So-Much
Web Scale
The Rise of NoSQL
Summary

2．Introducing Cassandra
The Cassandra Elevator Pitch
Cassandra in 50 Words or Less
Distributed and Decentralized
Elastic Scalability
High Availability and Fault Tolerance
Tuneable Consistency
Brewer's CAP Theorem
Row-Oriented
High Performance
Where Did Cassandra Come From?
Release History
Is Cassandra a Good Fit for My Project?
Large Deployments
Lots of Writes， Statistics， and Analysis
Geographical Distribution
Evolving Applications
Getting Involved
Summary

3．Installing Cassandra
Installing the Apache Distribution
Extracting the Download
What's In There?
Building from Source
Additional Build Targets
Running Cassandra
On Windows
On Linux
Starting the Server
Stopping Cassandra
Other Cassandra Distributioaas
Running the CQL Shell
Basic cqlsh Commands
cqlsh Help
Describing the Environment in cqlsh
Creating a Keyspace and Table in cqlsh
Writing and Reading Data in cqlsh
Summary

4．The Cassandra Query Language
The Relational Data Model
Cassandra's Data Model
Clusters
Keyspaces
Tables
Columns
CQL Types
Numeric Data Types
Textual Data Types
Time and Identity Data Types
Other Simple Data Types
Collections
User-Defined Types
Secondary Indexes
Summary
……

前言/序言

　　Cassandra was open-sourced by Facebook in July 2008. This original version of Cassandra was written primarily by an ex-employee from Amazon and one from Microsoft. It was strongly influenceyd by Dynamo， Amazon's pioneering distributed key/value database. Cassandra implements a Dynamo-style replication model with no single point of failure， but adds a more powerful "column family" data model.
　　I became involved in December of that year， when Rackspace asked me to build them a scalable database. This was good timing， because all of today's important open source scalable databases were available for evaluation， Despite initially having only a single major use case， Cassandra's underlying architecture was the strongest， and I
　　directed my efforts toward improving the code and building a community.
　　Cassandra was accepted into the Apache Incubator， and by the time it graduated in March 2010， it had become a true open source success story， with committers from Rackspace， Digg， Twitter， and other companies that wouldn't have written their own
　　database from scratch， but together built something important.
　　Today's Cassandra is much more than the early system that powered （and still powers） Facebook's inbox search; it has become "the hands-down winner for transaction
　　processing performance：' to quote Tony Bain， with a deserved reputation for reliability and performance at scale.
　　As Cassandra matured and began attracting more mainstream users， it became clear that there was a need for commeraal support; thus， Matt Pfeil and I cofounded Riptano in April 2010. Helping drive Cassandra adoption has been very rewarding， espeaally seeing the uses that don't get discussed in public.
　　Another need has been a book like this one. Like many open source projects， Cassandra's documentation has historically been weak. And even when the documentation
　　ultimately improves， a book-length treatment like this will remain useful.
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